Legal claims defining the scope of protection. Each claim is shown in both the original legal language and a plain English translation.
1. A method of pre-populating a call routing template based on natural language inputs comprising: receiving a natural language input from a user, wherein the natural language input includes a natural language element having an association with a telecommunications routing code, the telecommunications routing code associated with decision tree logic associating routing of incoming calls to a telecommunications number; selecting the telecommunications routing code based at least in part on the association; populating information for the user, the information including a translation and mapping of natural language, existing user records and usage data; populating the telecommunications routing code at a node of a call routing decision tree to generate a populated call routing decision tree comprising a call routing template; and providing the user with a report comprising statistics describing a utilization of the call routing template.
Telecommunications call routing. This invention addresses the challenge of efficiently configuring call routing systems using user-friendly natural language. The method involves receiving a natural language input from a user. This input contains a phrase or term that is linked to a specific telecommunications routing code. This routing code, in turn, is connected to a decision tree that dictates how incoming calls are directed to a telecommunications number. The system then identifies and selects the appropriate telecommunications routing code based on its association with the user's natural language input. Subsequently, it compiles and populates information for the user. This information includes a translation of the natural language input, a mapping of existing user records, and relevant usage data. The selected telecommunications routing code is then inserted into a specific point, or node, within a call routing decision tree. This action creates a completed call routing decision tree, which functions as a call routing template. Finally, the user is presented with a report that includes statistical data detailing how the generated call routing template has been utilized.
2. The method of claim 1 , wherein the natural language input is a text element.
A system and method for processing natural language inputs, particularly text elements, to extract structured data or perform specific actions. The invention addresses the challenge of interpreting unstructured natural language inputs, such as text, to derive meaningful and actionable information. The method involves receiving a natural language input, which is a text element, and analyzing it to identify relevant data or commands. This may include parsing the text to extract key information, such as entities, relationships, or instructions, and converting it into a structured format. The system may then use this structured data to perform tasks, such as generating responses, updating databases, or triggering automated processes. The method ensures accurate interpretation of text inputs by employing natural language processing techniques, including syntax and semantic analysis, to understand context and intent. The invention is applicable in various domains, such as customer service, data entry, and automated workflows, where converting unstructured text into structured data or actions is essential. The system may also include validation steps to confirm the accuracy of the extracted data or executed actions, ensuring reliability in real-world applications.
3. The method of claim 2 , wherein the text element is a scanned text element.
A system and method for processing scanned text elements in digital documents involves extracting and analyzing text from scanned images to improve document searchability and usability. The method includes capturing a scanned text element from a document image, where the text may be distorted or degraded due to scanning artifacts. The system applies optical character recognition (OCR) to convert the scanned text into machine-readable format, correcting errors introduced during scanning. The processed text is then indexed and stored in a searchable database, allowing users to query the document content efficiently. The method further includes enhancing the scanned text by applying noise reduction, contrast adjustment, and text alignment techniques to improve OCR accuracy. Additionally, the system may compare the scanned text against a reference text database to verify and correct errors. This approach ensures that scanned documents retain their searchability and usability, addressing challenges in digitizing physical documents while preserving their content integrity. The method is particularly useful in archival systems, legal document processing, and enterprise content management where scanned documents are frequently accessed.
4. The method of claim 1 , wherein the natural language input is a voice element.
A system and method for processing natural language inputs, particularly voice-based inputs, to generate structured data outputs. The technology addresses the challenge of converting unstructured voice commands or queries into a standardized format for further processing, such as database queries, automation tasks, or decision-making systems. The method involves receiving a voice element, which may include spoken words, phrases, or commands, and analyzing the audio input to extract linguistic and contextual information. This includes speech recognition to transcribe the voice element into text, followed by natural language processing (NLP) to parse the text for intent, entities, and relationships. The processed data is then converted into a structured format, such as a query language or API call, enabling integration with other systems. The method may also include error handling, such as correcting misrecognized words or disambiguating ambiguous phrases, to improve accuracy. The system can be applied in various domains, including virtual assistants, customer service automation, and smart home devices, where voice inputs are a primary means of interaction. The invention enhances efficiency by automating the conversion of voice inputs into actionable data, reducing manual intervention and improving user experience.
5. The method of claim 4 , wherein the voice element is obtained by voice recognition software.
The invention relates to a method for processing voice elements in a communication system, specifically addressing the challenge of accurately capturing and utilizing voice inputs in automated or digital communication environments. The method involves obtaining a voice element through voice recognition software, which converts spoken language into a digital format that can be analyzed or processed by a computing system. This step ensures that the voice input is accurately transcribed or interpreted, enabling further actions such as data extraction, command execution, or integration with other digital systems. The voice recognition software may employ techniques such as speech-to-text conversion, natural language processing, or pattern recognition to interpret the spoken input. The method may also include additional steps, such as validating the voice element against predefined criteria or integrating it with other data sources to enhance accuracy or functionality. By leveraging voice recognition technology, the method improves the efficiency and reliability of voice-based interactions in various applications, including virtual assistants, automated customer service, and voice-controlled devices. The invention aims to streamline voice processing workflows and reduce errors associated with manual transcription or interpretation.
6. The method of claim 1 , wherein the decision tree logic determines a call path taken by an incoming call to a termination number.
This invention relates to telecommunications systems, specifically methods for routing incoming calls to termination numbers. The problem addressed is the need for efficient and intelligent call routing based on predefined decision criteria. Traditional systems often rely on static routing rules, which lack flexibility and adaptability to dynamic conditions. The method involves using decision tree logic to analyze incoming calls and determine the optimal call path. The decision tree evaluates various factors, such as caller identity, time of day, network conditions, or subscriber preferences, to select the most appropriate termination number. This ensures calls are routed efficiently, reducing call drops, improving service quality, and optimizing network resources. The decision tree logic may incorporate multiple layers of criteria, allowing for complex routing scenarios. For example, a call may first be checked against a whitelist or blacklist, then evaluated based on available network paths, and finally directed to the most cost-effective or highest-quality termination point. The system dynamically adjusts routing decisions in real-time, adapting to changes in network conditions or subscriber behavior. This approach enhances call reliability, reduces operational costs, and improves user experience by ensuring calls are routed through the best available path. The method is particularly useful in telecom networks, call centers, and VoIP services where intelligent routing is critical for performance and efficiency.
7. The method of claim 1 , wherein the decision tree logic determines a call path taken by an incoming call based at least in part on a time of day the incoming call is received.
This invention relates to call routing systems that use decision tree logic to determine the path taken by an incoming call. The system addresses the problem of efficiently routing calls to the appropriate destination based on dynamic factors, such as the time of day the call is received. The decision tree logic evaluates the call's arrival time and selects a call path accordingly, ensuring calls are directed to the most suitable destination based on temporal conditions. For example, calls received during business hours may be routed to a primary support team, while after-hours calls may be directed to an automated system or an on-call specialist. The system may also incorporate additional decision criteria, such as caller identity, call type, or geographic location, to further refine routing decisions. By dynamically adjusting call paths based on time-sensitive factors, the system improves call handling efficiency and ensures callers are connected to the most appropriate resources. The invention is particularly useful in customer service, emergency response, and other environments where time-based routing enhances service quality and operational efficiency.
8. The method of claim 1 , wherein the decision tree logic determines a call path taken by an incoming call based at least in part on a geographic location of a device from which the incoming call is received.
This invention relates to call routing systems that use decision tree logic to determine the path of an incoming call based on the geographic location of the calling device. The system analyzes the caller's location data to select an appropriate call path, ensuring calls are routed efficiently to the correct destination. The decision tree logic evaluates multiple factors, including the geographic location, to make routing decisions. This approach improves call handling by dynamically adjusting routing based on real-time location data, reducing misrouted calls and enhancing service efficiency. The system may integrate with existing telecommunication networks to process and route calls according to predefined rules tied to geographic regions. By leveraging location-based routing, the invention optimizes call distribution, particularly in scenarios where regional handling or compliance with local regulations is required. The method ensures that calls are directed to the most suitable destination based on the caller's location, improving user experience and operational efficiency.
9. The method of claim 1 , wherein the decision tree logic determines a call path taken by an incoming call within a telecommunications system.
A method for call routing in telecommunications systems uses decision tree logic to determine the path of an incoming call. The decision tree evaluates call attributes such as caller identity, time of day, or network conditions to select an appropriate routing path. This ensures efficient call handling by directing calls to the most suitable destination, such as a specific agent, department, or service. The method may also integrate with other call processing systems to enhance routing decisions. By dynamically analyzing call data, the system optimizes call flow, reduces wait times, and improves overall network performance. The decision tree logic can be updated or modified to adapt to changing network conditions or business requirements, ensuring flexible and scalable call management. This approach enhances customer experience by ensuring calls are routed to the most relevant destination based on real-time data.
10. One or more non-transitory, computer-readable media comprising computer executable instructions that, when executed, cause at least one processor to perform actions comprising: receive a natural language input from a user, wherein the natural language input includes a natural language element having an association with a telecommunications routing code, the telecommunications routing code associated with decision tree logic associating routing of incoming calls to a telecommunications number; select the telecommunications routing code based at least in part on the association; populating information for the user, the information including a translation and mapping of natural language, existing user records and usage data; populate the telecommunications routing code at a node of a call routing decision tree to generate a populated call routing decision tree comprising a call routing template; and provide the user with a report comprising statistics describing a utilization of the call routing template.
This invention relates to a system for automating the creation and analysis of call routing templates in telecommunications networks. The problem addressed is the manual and error-prone process of configuring call routing logic, which often requires specialized knowledge of telecommunications codes and decision trees. The solution involves a software-based approach that interprets natural language inputs from users to generate and optimize call routing configurations. The system receives a natural language input from a user, which includes elements associated with telecommunications routing codes. These codes are linked to decision tree logic that determines how incoming calls are routed to specific numbers. The system selects the appropriate routing code based on the input's associations and then populates a call routing template by translating the natural language input, integrating existing user records, and incorporating usage data. This template is structured as a decision tree, where the routing code is placed at a specific node to define the routing logic. The system then provides the user with a report containing statistics on the utilization of the generated call routing template, allowing for performance analysis and optimization. By automating the mapping of natural language inputs to routing configurations and providing usage analytics, the system simplifies the setup and management of call routing systems, reducing errors and improving efficiency.
11. The one or more non-transitory, computer-readable media of claim 10 , wherein the natural language input is a text element.
The invention relates to natural language processing systems that analyze user inputs to generate structured data. The problem addressed is the difficulty of accurately interpreting unstructured natural language inputs, such as text, to extract meaningful information for further processing or decision-making. The system processes a natural language input, such as a text element, to identify relevant entities, relationships, or actions within the input. It then converts this unstructured data into a structured format, such as a knowledge graph or database schema, enabling automated reasoning, query processing, or integration with other systems. The system may use machine learning models, rule-based parsing, or hybrid approaches to analyze the input and extract structured data. The structured output can be used for tasks like information retrieval, decision support, or data integration across different applications. The invention improves the efficiency and accuracy of natural language understanding by providing a standardized way to convert unstructured text into a machine-readable format, reducing manual intervention and enhancing automation in data processing workflows.
12. The one or more non-transitory, computer-readable media of claim 11 , wherein the text element is a scanned text element.
A system and method for processing scanned text elements in a document processing application. The invention addresses the challenge of accurately extracting and analyzing text from scanned documents, which often contain noise, distortions, or formatting inconsistencies that complicate automated processing. The system includes a computer-readable medium storing instructions that, when executed, perform operations to identify and process text elements within a scanned document. The text elements are extracted from the scanned image using optical character recognition (OCR) techniques, and the system further analyzes the extracted text to determine its structure, content, and relevance. The processed text elements can then be used for various applications, such as document indexing, search, or data extraction. The invention improves upon existing OCR systems by incorporating advanced image preprocessing techniques to enhance text recognition accuracy and reduce errors caused by poor scan quality or complex layouts. Additionally, the system may include machine learning models trained to recognize and correct common OCR errors, further improving the reliability of the extracted text. The invention is particularly useful in applications requiring high-accuracy text extraction from scanned documents, such as legal, medical, or financial document processing.
13. The one or more non-transitory, computer-readable media of claim 10 , wherein the natural language input is a voice element.
This invention relates to systems for processing natural language inputs, particularly voice-based inputs, in computing environments. The technology addresses the challenge of accurately interpreting and responding to voice commands or queries in applications such as virtual assistants, automated customer service, or voice-controlled devices. The system captures a voice input from a user, converts it into a structured format, and processes it to extract meaningful data or execute specific actions. The voice element may include spoken words, phrases, or commands, which are analyzed to determine intent, context, or required actions. The system may then generate a response, trigger a function, or retrieve relevant information based on the interpreted voice input. This approach enhances user interaction by enabling hands-free, intuitive control of devices or applications through natural language processing (NLP) techniques. The invention improves upon existing methods by optimizing voice recognition accuracy and response efficiency, making it suitable for real-time applications where quick and precise interpretation of spoken language is critical.
14. The one or more non-transitory, computer-readable media of claim 13 , wherein the voice element is obtained by voice recognition software.
The invention relates to a system for processing voice elements in a computing environment. The problem addressed is the need for accurate and efficient extraction of voice elements from audio data, particularly in applications requiring automated analysis or interaction. The system involves obtaining a voice element from audio data using voice recognition software, which converts spoken language into text or other machine-readable formats. This allows for further processing, such as natural language understanding, speech synthesis, or integration with other digital systems. The voice recognition software may employ techniques like acoustic modeling, language modeling, or deep learning to improve accuracy. The extracted voice element can then be used in various applications, such as virtual assistants, transcription services, or voice-controlled interfaces. The system ensures that voice data is accurately captured and processed, enabling seamless interaction between users and digital systems. The invention focuses on leveraging advanced voice recognition to enhance the reliability and functionality of voice-based technologies.
15. The one or more non-transitory, computer-readable media of claim 10 , wherein the decision tree logic determines a call path taken by an incoming call to a termination number.
The invention relates to telecommunications systems, specifically to routing incoming calls to termination numbers using decision tree logic. The problem addressed is the need for efficient and flexible call routing based on predefined criteria to optimize call handling and resource allocation. The system involves a computer-readable medium storing instructions for processing calls. The decision tree logic evaluates incoming calls to a termination number and determines the appropriate call path based on predefined rules. These rules may consider factors such as caller identity, time of day, network conditions, or other contextual data. The logic dynamically selects the optimal routing path to ensure calls are directed to the most suitable destination, improving call efficiency and user experience. The decision tree logic may also integrate with other call processing components, such as call forwarding, call screening, or call prioritization modules, to enhance routing decisions. The system ensures that calls are routed according to the most current and relevant criteria, adapting to changing conditions in real time. This approach reduces call failures, minimizes latency, and optimizes network resource usage. The invention is particularly useful in telecommunications networks, call centers, and enterprise communication systems where efficient call routing is critical.
16. The one or more non-transitory, computer-readable media of claim 10 , wherein the decision tree logic determines a call path taken by an incoming call based at least in part on a time of day the incoming call is received.
This invention relates to call routing systems that use decision tree logic to determine the path taken by an incoming call. The problem addressed is the need for intelligent call routing that adapts to dynamic conditions, such as the time of day, to improve call handling efficiency and customer experience. The system involves a decision tree logic that evaluates multiple factors to route calls. In this specific implementation, the decision tree logic considers the time of day the call is received as a key factor in determining the call path. This allows the system to direct calls to different destinations based on time-based rules, such as routing calls to a 24/7 support line during off-hours or to a specialized team during peak business hours. The decision tree logic may also incorporate other factors, such as caller identity, call type, or system load, to further refine routing decisions. The system is implemented using non-transitory, computer-readable media that store instructions for executing the decision tree logic. The logic processes incoming call data, applies predefined rules, and selects an appropriate call path based on the evaluated conditions. This approach ensures that calls are routed optimally, reducing wait times and improving resource allocation. The invention enhances traditional call routing by introducing time-based intelligence, making it particularly useful for businesses with varying support needs throughout the day.
17. The one or more non-transitory, computer-readable media of claim 10 , wherein the decision tree logic determines a call path taken by an incoming call based at least in part on a geographic location of a device from which the incoming call is received.
This invention relates to call routing systems that use decision tree logic to determine the path of an incoming call based on the geographic location of the calling device. The system processes incoming calls by analyzing the geographic location data associated with the device initiating the call. The decision tree logic evaluates this location data to select an appropriate call path, which may direct the call to different destinations, such as specific call centers, service providers, or regional offices. The system may also incorporate additional factors, such as call type or time of day, to further refine the routing decision. The geographic location data can be obtained from the device's GPS coordinates, IP address, or other location-identifying information. The decision tree logic applies predefined rules or algorithms to map the location data to the most suitable call path, ensuring efficient and context-aware call handling. This approach improves call routing accuracy and reduces the need for manual intervention, enhancing overall system performance and user experience. The invention is particularly useful in telecommunications, customer service, and emergency response systems where location-based routing is critical.
18. The one or more non-transitory, computer-readable media of claim 10 , wherein the decision tree logic determines a call path taken by an incoming call within a telecommunications system.
A system and method for call routing in telecommunications networks uses decision tree logic to determine the path of an incoming call. The system processes call data, such as caller identity, time of day, and network conditions, to evaluate predefined rules stored in a decision tree structure. The decision tree logic applies these rules sequentially to classify the call and select an appropriate routing path. This ensures efficient call handling by dynamically adapting to real-time conditions and caller-specific requirements. The system may also integrate with external databases or APIs to retrieve additional context, such as subscriber preferences or service availability, to refine routing decisions. The decision tree logic can be updated dynamically to accommodate changes in network policies or service offerings. This approach improves call routing accuracy, reduces latency, and enhances overall network performance by optimizing resource allocation and minimizing unnecessary call transfers. The system is particularly useful in large-scale telecommunications networks where efficient call handling is critical for maintaining service quality and customer satisfaction.
19. The one or more non-transitory, computer-readable media of claim 10 , wherein the decision tree logic determines a call path taken by an incoming call based at least in part on a specified call volume threshold.
A system for managing call routing in a telecommunications network addresses the challenge of efficiently distributing incoming calls to available agents or resources. The system uses decision tree logic to analyze call characteristics and determine the optimal call path. This logic evaluates factors such as call volume, agent availability, and priority levels to route calls effectively. A key feature is the ability to adjust routing decisions based on a specified call volume threshold. When call volume exceeds this threshold, the system may prioritize certain call paths, redirect calls to alternative resources, or implement load-balancing strategies to prevent system overload. The decision tree logic may also incorporate additional criteria, such as caller identity, time of day, or service type, to further refine routing decisions. The system dynamically adapts to changing call volumes and network conditions, ensuring efficient call handling and minimizing wait times. This approach improves resource utilization and enhances customer service by ensuring calls are routed to the most appropriate destination based on real-time conditions.
20. The one or more non-transitory, computer-readable media of claim 10 , wherein the decision tree logic determines a call path taken by an incoming call based at least in part on a geographic location associated with a termination number.
This invention relates to call routing systems that use decision tree logic to determine call paths based on geographic location data associated with termination numbers. The system processes incoming calls by analyzing the geographic location linked to the called number, then applies decision tree logic to route the call through a specific path. The decision tree logic evaluates multiple factors, including the geographic location, to select the optimal call path. This approach improves call routing efficiency by dynamically adjusting paths based on real-time location data, reducing latency and optimizing network resource usage. The system may also integrate with other call processing features, such as call forwarding or number portability, to enhance routing flexibility. The geographic location data can be derived from the termination number itself or from additional databases that map numbers to locations. This method ensures calls are routed through the most efficient network paths, improving call quality and reducing operational costs. The invention is particularly useful in telecommunications networks where dynamic routing based on geographic data is critical for performance optimization.
Unknown
July 7, 2020
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